|Open Access Gold|
Integrative analysis of MicroRNA and mRNA data reveals an orchestrated function of MicroRNAs in skeletal myocyte differentiation in response to TNF-α or IGF1.
PLoS ONE 10:e0135284 (2015)
INTRODUCTION: Skeletal muscle cell differentiation is impaired by elevated levels of the inflammatory cytokine tumor necrosis factor-α (TNF-α) with pathological significance in chronic diseases or inherited muscle disorders. Insulin like growth factor-1 (IGF1) positively regulates muscle cell differentiation. Both, TNF-α and IGF1 affect gene and microRNA (miRNA) expression in this process. However, computational prediction of miRNA-mRNA relations is challenged by false positives and targets which might be irrelevant in the respective cellular transcriptome context. Thus, this study is focused on functional information about miRNA affected target transcripts by integrating miRNA and mRNA expression profiling data. METHODOLOGY/PRINCIPAL FINDINGS: Murine skeletal myocytes PMI28 were differentiated for 24 hours with concomitant TNF-α or IGF1 treatment. Both, mRNA and miRNA expression profiling was performed. The data-driven integration of target prediction and paired mRNA/miRNA expression profiling data revealed that i) the quantity of predicted miRNA-mRNA relations was reduced, ii) miRNA targets with a function in cell cycle and axon guidance were enriched, iii) differential regulation of anti-differentiation miR-155-5p and miR-29b-3p as well as pro-differentiation miR-335-3p, miR-335-5p, miR-322-3p, and miR-322-5p seemed to be of primary importance during skeletal myoblast differentiation compared to the other miRNAs, iv) the abundance of targets and affected biological processes was miRNA specific, and v) subsets of miRNAs may collectively regulate gene expression. CONCLUSIONS: Joint analysis of mRNA and miRNA profiling data increased the process-specificity and quality of predicted relations by statistically selecting miRNA-target interactions. Moreover, this study revealed miRNA-specific predominant biological implications in skeletal muscle cell differentiation and in response to TNF-α or IGF1 treatment. Furthermore, myoblast differentiation-associated miRNAs are suggested to collectively regulate gene clusters and targets associated with enriched specific gene ontology terms or pathways. Predicted miRNA functions of this study provide novel insights into defective regulation at the transcriptomic level during myocyte proliferation and differentiation due to inflammatory stimuli.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Growing Neural-network; Muscle Differentiation; Myogenic Differentiation; Myoblast Differentiation; Expression Data; Growth-factors; Proliferation; Targets; Myod; Regeneration
ISSN (print) / ISBN 1932-6203
Zeitschrift PLoS ONE
Quellenangaben Band: 10, Heft: 8, Artikelnummer: e0135284
Verlagsort Lawrence, Kan.
Institut(e) Institute of Computational Biology (ICB)